In today’s hyper-competitive global marketplace, the speed at which organizations can move a product from concept to customer often determines their ability to lead, survive, or fade away. Traditionally, product development lifecycles were measured in quarters or even years, with countless manual processes, capacity bottlenecks, and unforeseen delays. Now, Artificial Intelligence (AI) is unleashing a new era-where accelerated, data-driven development translates into shorter time to market, greater innovation, and a decisive competitive advantage.

But how exactly is AI achieving these outcomes, and what should companies focus on to leverage this transformation? Let’s dig deeper.

The Challenge: Speed vs. Complexity

Before exploring AI’s impact, it’s important to recognize the forces at play in modern product development:

Within this context, accelerating time to market isn’t just about working harder or hiring more people. It’s about working smarter-streamlining decision making, eliminating friction, and uncovering opportunities that humans alone might miss.

Where AI Drives Acceleration

1. Ideation and Market Sensing

The earliest phase – identifying promising ideas and market needshas been famously uncertain. AI is shifting this through:

Example: Consumer electronics firms now use AI to predict product features likely to drive adoption by processing social data and e-commerce feedback in real time.

2. Design and Prototyping

Designing products is inherently creative-but AI is making it faster and smarter:

Example: In automotive, generative design led to new lightweight parts, engineered by AI, reducing prototyping cycles from months to days.

3. Streamlined Project Management

Staying on schedule requires real-time awareness and decision making. AI-driven platforms now:

Example: In pharmaceutical development, AI helped identify clinical trial sites with the highest odds of on-time recruitment, compressing overall timelines by months.

4. Supply Chain and Manufacturing

Manufacturing schedules and component delivery were historically the biggest cause of launch delays. Here, AI excels at:

Example: Companies like Siemens use AI-based digital twins of factories to simulate production runs and identify process optimizations before going live.

5. Quality Assurance

Manual quality assurance is slow and error prone. AI improves this through:

Example: In electronics, AI-based visual inspectors reduced defect rates by over 50%, enabling safe acceleration of assembly lines.

6. Continuous Feedback and Improvement

Post-launch, AI keeps products competitive:

Key Success Factors for AI-Driven Time to Market

a) Data Quality and Integration

AI’s effectiveness depends on access to clean, relevant data-across engineering, supply chain, customer service, and more. Integrating siloed systems is foundational.

b) Talent and Human-AI Collaboration

AI accelerates, but humans remain essential for strategy, creativity, and ethical oversight. The most effective companies pair “citizen data scientists” and AI specialists with product managers and engineers.

c) Continuous Process Optimization

Organizations that systematically embed AI into their PLM (Product Lifecycle Management), ERP (Enterprise Resource Planning), and SCM (Supply Chain Management) platforms gain compounding benefits over time.

Risks and Considerations

While the upside of AI in reducing time to market is massive, organizations must manage:

Looking Forward

The pace of innovation will only accelerate, with AI at its core. Soon, entirely digital product twins-learning and optimizing themselves-will make it possible to conceptualize, design, test, and manufacture new products in a continuous, AI-powered loop.

Leaders who invest now in AI, data integration, and team capabilities will not only improve time to market-they’ll redefine what’s possible and lead their industries into the future.

Conclusion:

Artificial Intelligence is revolutionizing every stage of the product development journey. From ideation to design, project management, supply chain, and quality assurance, AI is the accelerator pedal companies need to stay ahead in a fast-moving world. By embracing AI not just as a tool, but as a core capability, businesses can achieve breakthrough speed, higher quality, and lasting competitive advantage.

About the Author:

Mr. Vivek Agarwal brings more than 15 years of consulting experience spanning product lifecycle management (PLM), digital transformation, and data-led operations.

Mr. Vivek Agarwal’s career includes leadership and consulting roles with Deloitte, Capgemini, Accenture, Tata Consultancy Services, and Saiana Technologies, supporting complex engineering and R&D transformations across automotive, aerospace, high tech, and medical devices. He is recognized for guiding organizations through capability maturation, value mapping, and end‑to‑end process redesign across PLM platforms such as SAP PLM, 3DEXPERIENCE, Teamcenter, and Oracle Agile.

Mr. Vivek Agarwal skills portfolio spans cybersecurity and cryptography for engineering data, secure data exchange (CAD, BOMs, digital twins), data privacy and governance, and regulatory frameworks (GDPR, NIST, ISO 27001)—all anchored in collaborative delivery with product engineering, IT security, and product management teams.

Beyond client work, Mr. Vivek Agarwal thought leadership has been cited in academic literature on supply chain dynamics for 3‑D printed products, underscoring a blend of practical impact and research‑aware perspective.

Mr. Vivek Agarwal can be contacted at:

LinkedIn | Website | E-mail

Mr. Vivek Agarwal is Bestowed with the following Licenses & Certifications :

https://www.linkedin.com/in/agrawalvivek/details/certifications/

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Simple products don’t just feel better to use. They are safer to use.
Clear language doesn’t just improve usability. It actively blocks deception.

When UI, UX, and cybersecurity work together, something powerful happens: users make fewer mistakes, attackers lose leverage, and risk quietly drops. This connection is still underestimated, but it’s one of the most effective defenses we have.

The uncomfortable truth about cyber risk

Not every security incident begins with a brilliant hacker. Many start with something far more ordinary: a confusing screen, an unclear action, or an interface that forces people to guess.

When people don’t understand what a system is asking them to do, they improvise. And improvisation is dangerous in digital environments.

A poorly designed interface doesn’t just slow users down, it nudges them toward errors. A vague button, a misleading confirmation message, or a cluttered layout can become the weakest link in an otherwise strong security setup.

Good design quietly prevents problems. Bad design quietly creates them.

That’s why this relationship deserves attention.

“The safest digital products aren’t the most complex. They’re the ones that remove doubt. At AV DESIGNS, we design experiences that feel clear, familiar, and trustworthy, because confidence is the first layer of security.”

Cybersecurity has moved beyond the IT department

For years, organizations treated security as a backend concern. Firewalls, encryption, access controls, important, but invisible. Design lived elsewhere. UX was about ease. UI was about appearance.

That separation no longer works.

Today, a confusing interface can cause more damage than a technical vulnerability. Users don’t think in silos. They respond to what they see, what feels familiar, and what looks trustworthy on screen.

If an action isn’t clearly explained, users guess.
If a warning looks generic, they dismiss it.
If a security message feels abrupt or unclear, they ignore it.

Modern cybersecurity includes visual clarity, behavioral guidance, and communication that reduces hesitation, not just infrastructure.

Because the largest source of cyber incidents isn’t technology. It’s human error. And design has enormous influence over human behavior.

Why people make mistakes online?

People don’t analyze interfaces the way designers or security professionals do. They skim. They rely on patterns. They assume things work the way they worked last time.

No one carefully reads every permission request. No one double-checks URLs under pressure. No one studies warning messages when they’re trying to finish a task quickly.

Attackers understand this perfectly.

They don’t rely on technical brilliance alone. They rely on familiarity. If something looks close enough to what users expect, the brain fills in the gaps.

This is where inconsistent or messy design becomes a real liability.

When your legitimate screens lack consistency, different layouts, shifting styles, unclear messaging, it becomes easier for fake screens to blend in. If your real interface is already confusing, users have no reliable mental model to compare against.

Consistency isn’t just a brand choice. It’s a security signal.

When design inconsistency enables phishing?

Picture this.

A customer receives a genuine login alert from your platform. The email layout doesn’t quite match the website. The color palette is slightly different. The tone feels unfamiliar.

The next day, they receive a phishing email. It looks similar enough, because your real communication didn’t have a strong, recognizable pattern to begin with.

Now the user hesitates. Or worse, they don’t.

Nothing failed technically. But trust collapsed.

Strong, predictable design makes fake messages stand out. Weak identity makes imitation effortless.

Design protects when it’s consistent, intentional, and recognizable. It becomes a vulnerability when it’s loose and undefined.

Simplicity is an underrated security control

Every additional option increases cognitive load.
Every extra step increases fatigue.
Every unnecessary element increases the chance of error.

When interfaces become dense, users rush. When users rush, they stop evaluating risk.

Think about common security flows like password resets or account recovery. A clear, short, well-guided flow encourages safe behavior. A long, confusing one encourages shortcuts, password reuse, skipped steps, careless clicks.

Design doesn’t just support behavior. It shapes it.

Simplicity isn’t about minimal aesthetics. It’s about reducing the number of ways things can go wrong.

Labels can either protect users, or trap them

Language matters more than most teams realize.

A button that says “Continue” asks the user to trust blindly. Continue to what? A payment? A deletion? A verification step?

Clear labels remove ambiguity. They tell users exactly what will happen next, which removes the attacker’s advantage.

When actions are explicitly named, manipulation becomes harder. Deception thrives in vagueness. Clarity shuts it down.

Good labels guide users forward. Bad labels force them to guess.

Designing with phishing in mind

Phishing works by exploiting uncertainty. Attackers depend on users being unable to quickly tell what’s real.

Clean, consistent UI makes that difficult.

When real interfaces follow strict visual and behavioral rules, colors, typography, spacing, tone, users develop intuition. Anything that breaks the pattern feels wrong.

Consistency trains users what to trust. Inconsistency trains them to ignore warning signs.

Well-designed products don’t need loud alerts to be safe. They rely on familiarity, predictability, and subtle cues that the brain recognizes instantly.

UX decisions that quietly strengthen security

Some of the most effective security reinforcements don’t look like security at all:

• Real-time feedback that catches errors early
• Step-by-step flows that remove guesswork
• Safe defaults that protect users without effort
• Visual cues that signal legitimacy
• Familiar interaction patterns that reduce hesitation

When experiences feel smooth, users behave more carefully. When experiences feel chaotic, users stop paying attention.

Ease and safety are not opposites. They reinforce each other.

How does poor UX lead to security fatigue?

Constant alerts, unclear warnings, and complicated processes wear people down. Over time, users stop reading. They approve requests automatically. They click through messages just to get them out of the way.

This isn’t user negligence. It’s fatigue caused by design.

People don’t dislike security. They dislike confusing, interruptive, badly explained security.

Thoughtful design reduces friction without removing protection. It keeps users engaged instead of exhausted.

Microcopy: the smallest, strongest defender

A few words can completely change how a user reacts.

Clear, human language builds confidence. Confusing language creates hesitation or blind trust, both dangerous.

Microcopy explains intent. It tells users why something is happening, not just what to click. That understanding is often enough to prevent a mistake.

Words guide behavior. Behavior determines risk.

Subtle design choices that lower risk

Many protective design decisions are quiet:

• Visual password strength indicators
• Confirmation summaries before critical actions
• Plain-language warnings instead of technical jargon
• Tooltips that explain data usage
• Strongly branded verification screens
• Email designs that are hard to imitate
• Controlled color usage so anomalies stand out
• Adequate spacing to prevent accidental clicks

Good design doesn’t shout. It is reassuring.

Why do security teams need designers at the table?

Security professionals understand threats. Designers understand behavior. UX teams understand friction.

When these perspectives stay separate, gaps appear. When they work together, those gaps close.

Modern security isn’t just engineered. It’s designed.

Designing safer digital experiences by default

Organizations that take this seriously build safety into their systems:

• Strong, consistent brand identity
• Clear, intuitive user flows
• Predictable layouts
• Explicit labels
• Visual guidance instead of guesswork
• Human language in security messages
• Testing for confusion, not just beauty
• Reduced clutter
• Elevated visual treatment for critical actions
• Trust treated as a core design principle

Security becomes part of the experience, not an afterthought.

Where is this all heading?

As AI-powered scams, deepfake interfaces, and hyper-realistic phishing increase, technical defenses alone won’t be enough.

Clarity will matter more than complexity.
Recognition more than warnings.
Design more than detection.

Design will become the first line of defense.

The real takeaway

Many cyber risks don’t begin with malicious code. They begin with uncertainty. And uncertainty often begins with design.

Clear interfaces reduce mistakes. Clear language limits deception. Consistent patterns build trust. Thoughtful UX guides safer behavior.

Bad design isn’t just inconvenient. It’s risky.

If you want safer users, design with clarity.
If you want fewer incidents, reduce complexity.
If you want stronger cybersecurity, start with UI and UX.

Because when people feel confident, they act carefully.
And that’s the quiet power of good design.

About the Author:

Mr. Aswin Vijayan
Brand Consultant – AV DESIGNS

Aswin Vijayan is a creative strategist and founder of AV DESIGNS, with 15+ years of experience in design, UX, SEO, and digital marketing. His work focuses on building user-centric digital experiences that blend creativity, clarity, and performance.

His journey began in 2009, driven by a deep curiosity for visual storytelling and digital creativity. Starting with logos, icons, and photo manipulation, Aswin quickly expanded into web design, HTML development, and freelance projects working closely with early-stage businesses to shape their digital identities from the ground up.

By 2014, his growing expertise led to the launch of his first official website, marking a shift from individual projects to a more structured creative practice. Soon after, working within a company environment gave him real-world exposure to business operations, client expectations, and the strategic role design plays in growth and decision-making.

Over the years, Aswin’s focus evolved beyond aesthetics. Through continuous self-learning and experimentation, he developed strong expertise in branding, digital marketing, SEO, UX design, and performance-driven design systems, allowing him to connect creativity with measurable outcomes.

Today, Aswin leads AV DESIGNS, a full-service creative and digital agency supported by a global team of designers, developers, and marketers. His work centers on building clear, intuitive, and scalable digital experiences where design is not just visual, but strategic, functional, and impactful.

Aswin Vijayan can be contacted at:

LinkedIn | X | Website | E-mail | Technical Influencer

AV DESIGNS can be contacted at:

LinkedIn | X | Instagram | FaceBook | Website

The post How Design Choices Can Reduce Cybersecurity Risks? appeared first on Industry4o.com.

Some 5000 years ago, the Sumerians living in ancient Mesopotamia, the rich, fertile lands that today comprise modern Iraq, gave to the world a revolution in its most basic measure: time. The sexagesimal number advancement, based on the number 60, was their most advanced; this was a superior numbering system. That innovative structure meant that an hour was broken down into 60 minutes and each minute subdivided into the fundamental second; the features that represent the very essence of the contemporary practice of keeping time.

Much of the motivation for such developments in time-keeping was the agricultural lifestyle in which the Sumerians lived: an accurate calendar was necessary to enable timely planting and harvesting of crops and sufficient organization of the varied religious rituals and administrative works.

The Sumerians advanced significantly beyond mere measured time, indeed never wanted instead to watch the movements of heavenly bodies. They accumulated quite a bit of data on celestial movements and could construct a calendar of 12 months that associated closely with the agricultural seasons.

Of course, to have reasoned out the structure of a day into 24 hours, an hour into 60 minutes, and a minute into 60 seconds is surely an incredible achievement. These divisions were devised for purposes of practicality and ease of use; that is, in short-sighted manner, in terms of the Sumerians’ knowledge of mathematics.

This technological system was important from that point on created by the Babylonians and the Greeks and eventually even landed in the Roman civilization. The Sumerians have thus left the imprint of their day-based central system on all clocks and calendars today, retelling the story of a great deal that this innovation did for countless lives.

The Sumerians are considered the first urban civilization (along with that of ancient Egypt and the Indus Valley), which lived south of Mesopotamia (today’s south-eastern Iraq), between the Tigris and Euphrates rivers. This region, often referred to as the cradle of civilization, was home to many firsts in human history, including the invention of writing, the wheel, and notably as we’ve seen, the concept of timekeeping.

The Sumerians’ division of time was not just a mathematical feat but also a practical tool that facilitated their daily lives and societal functions. Their 12-month lunar calendar was meticulously aligned with the agricultural seasons, ensuring that planting and harvesting were done at optimal times. This calendar was also crucial for scheduling religious festivals and administrative activities, which were integral to Sumerian society.

Their achievements were no less remarkable with regards to astronomy: The Sumerians watched the movements of celestial bodies and were able to see the seasons change as well as predict celestial phenomena and improve their calendar and timekeeping practices. This astronomical knowledge was passed down to later civilizations who further advanced the art of keeping time.

Significant, indeed, was Sumerian time keeping because its sexagesimal system formed the foundation of the modern method of measuring time. The measuring of a day in 24 hours, an hour by 60 minutes, and a minute by 60 seconds reflects both their highly developed mathematical understanding and their practical aspect of solving problems. This was a feature that other succeeding civilizations (including those of the Babylonians, the Greeks, and later, the Romans) adopted, built upon, and made into one of the cornerstones of timekeeping in this modern world.

This is also how Sumerian timekeeping illustrates the act of transformation ancient innovations can achieve in human civilization: Apt measurement and proper record keeping provided a basis for complex later societies, which indeed shows the long-lasting effects of ancient creativity.

From time to time, the Sumerians would change their timekeeping to accommodate their innovative methods; today, new data visualization tools are changing the way we think about strategic decision-making. Both of these advances consolidate understanding and orderliness in difficult systems. They were thereby enabled to bring all their activities up to two times in their year of harvests, religious rituals, and other government undertakings for greater synchronization and still higher efficiency and productivity.

In much the same way, data visualization processes for navigating the complexities created by a data-rich environment toward clear and actionable insights.  This modern innovation parallels the Sumerians’ systematic approach, particularly in three key areas that enhance organizational efficiency. Furthermore, these visualization capabilities lay the groundwork for effective team communication, much as the Sumerian calendar system facilitated societal coordination.

Meaningful Goal Clarification: Understanding your end goal is a must when it comes to making complicated decisions. Data visualization helps map key performance indicators and objectives in a format that is visually accessible. This includes things like progress dashboards or goal-oriented graphs that make it immediately evident whether or not you’re headed in the right direction. Noticing how different data points are relating to your strategic goals can help you prioritize actions that will make the highest impact. For example, a dashboard showing sales performance against targets could show places needing attention faster so they might take corrective action more quickly.

Recognizing Patterns: Data visualization opens up the doors to reveal well-guarded patterns that may otherwise remain hidden from the eyes of a data analyst. For example, a line graph can show trends over time while a heat map can signify areas that have high activity or areas that are of concern. Therefore, being able to recognize these patterns further enables strategic decision-making in anticipation of possible scenarios and making necessary preparations. For instance, trend analysis of customer behavior can give insight into when inventory needs to be increased and decreased with seasonal peaks and troughs, as well as marketing efforts.

Enhancing Communication: This is one of the features data visualization adds to communications of team members. Very many people, regardless of their expertise, can grasp some of the complex data from a well-designed chart or graph easily. This common visual language enables teams to collaborate more effectively, discuss strategic options with a clear understanding of the data, and reach consensus more quickly. For example, a pie chart showing the distribution of project resources can help team members understand resource allocation and identify areas for improvement.

Effective Data Analytics Team Communication

Just as the Sumerians’ timekeeping innovations facilitated better societal coordination and communication, modern data analytics teams require sophisticated communication strategies to maximize their effectiveness. The visualization tools we’ve discussed serve as a bridge to understanding, but emotional intelligence plays an equally crucial role in translating that understanding into collaborative success. How is this accomplished?

Encouraging an Open Environment

First, create a theme so that team members can freely express themselves about their ideas, concerns, and emotions. An example of this could be regular team meetings or just casual ones with open discussions. Such behavior will make people feel heard and valuable, trust-building, and less tension-causing. Some examples would use facilitation techniques like round-robin discussions or anonymous feedback tools to ensure all voices are included, even those who might be hesitant to speak up.

Cultivating Effective Listening

According to this definition, talking does not encapsulate communication but includes listening. People must be encouraged to practice active listening to share messages with others by really focusing on the speaker and channeling their points while asking for clarifications when need be. The resulting outcome is aversion to incorrect assumptions of intended messages and a means to communicate regarding the worth of everyone involved. You may even set up workshops or training sessions about effective listening and empathy towards raising emotional intelligence across the entire team.

Building a Culture of Feedback

Create a culture in which feedback becomes commonplace and invited. Constructive feedback should be constructive, respectful, and behavior or process-focused rather than personality-focused. Communication like this will help make team members cognizant of how their behavior affects others and inspire them to think more about how they act. You build a feedback-rich environment; the team will be more self-aware and better able to respond.

Fostering Empathy Through Collaboration

Finally, design collaborative activities or cross-functional projects where team members must rely on one another’s expertise. This not only improves technical skills but also builds empathy, as members learn to appreciate the unique challenges and contributions of their peers. When team members recognize the value each person brings, it naturally fosters a more supportive and emotionally intelligent atmosphere.

Conclusion: Elevating Team Dynamics Through Better Communication

To summarize, improving communication within your data analytics team is a strategic approach to enhancing emotional intelligence, much like how the Sumerians’ systematic approach to timekeeping enhanced societal coordination. Fostering an open environment, cultivating effective listening, building a feedback culture, and encouraging empathy through collaboration will enable you to transform how your team interacts, ultimately leading to more cohesive and productive outcomes.

In conclusion, just as the Sumerians revolutionized timekeeping with their innovative approach, modern data visualization tools are transforming the way we make strategic decisions. For one thing, clarity about objectives; awareness about kinds of patterns; increased communication–these, among others, are what data visualization brings into the present dilemma of every person in a highly compressed data environment. Use these implements to create informed decisions, increased efficiency, and better results for your organization. In fact, the memory of Sumer can remind us that innovation in what we measure and how we make sense of it can have a really profound and lasting effect on our way of living.

And who knows? Maybe 5,000 years from now, future civilizations will look back at our data visualization tools with the same reverence we hold for the Sumerians’ 60-minute hour – though hopefully they will have figured out a way to make their Monday morning meetings feel shorter than an eternity!

“Bringing Data to Life and Life to Data”

About the Author:

Dr. Joe Perez,
Team Lead / Senior Systems Specialist,
NC Department of Health and Human Services

Dr. Joe Perez ( Dr.Joe ) is also the Chief Technology Officer – CogniMind

To book Dr. Joe Perez for your speaking engagement please click here

Dr. Joe Perez was selected as the 2023 Gartner Peer Community Ambassador of the Year.

Dr. Joe Perez is a truly exceptional professional who has left an indelible mark on the IT, health and human services, and higher education sectors. His journey began in the field of education, where he laid the foundation for his career. With advanced degrees in education and a doctorate that included a double minor in computers and theology, Joe embarked on a path that ultimately led him to the dynamic world of data-driven Information Technology.

In the early 1990s, he transitioned into IT, starting as a Computer Consultant at NC State University. Over the years, his dedication and expertise led to a series of well-deserved promotions, culminating in his role as Business Intelligence Specialist that capped his 25 successful years at NC State. Not one to rest on his laurels, Dr. Perez embarked on a new challenge in the fall of 2017, when he was recruited to take on the role of Senior Business Analyst at the NC Department of Health & Human Services (DHHS). His impressive journey continued with promotions to Senior Systems Analyst and Team Leader, showcasing his versatility and leadership capabilities.

In addition to his full-time responsibilities at DHHS, Joe assumed the role of fractional Chief Technology Officer at a North Carolina corporation in October 2020. A top-ranked published author with over 18,000 followers on LinkedIn and numerous professional certifications, he is a highly sought-after international keynote speaker, a recognized expert in data analytics and visualization, and a specialist in efficiency and process improvement.

Dr. Perez’s contributions have not gone unnoticed. He is a recipient of the IOT Industry Insights 2021 Thought Leader of the Year award and has been acknowledged as a LinkedIn Top Voice in multiple topics. He holds memberships in prestigious Thought Leader communities at Gartner, Coruzant Technologies, DataManagementU, Engatica, the Global AI Hub, and Thinkers360 (where he achieved overall Top 20 Thought Leader 2023 ranking in both Analytics and Big Data). His reach extends to more than twenty countries worldwide, where he impacts thousands through his speaking engagements.

Beyond his professional achievements, Joe’s passion for teaching remains undiminished. Whether as a speaker, workshop facilitator, podcast guest, conference emcee, or team leader, he continually inspires individuals to strive for excellence. He treasures his time with his family and is a gifted musician, singer, pianist, and composer. Joe also dedicates his skills as a speaker, interpreter, and music director to his church’s Hispanic ministry. He manages the publication of a widely recognized monthly military newsletter, The Patriot News, and is deeply committed to his community.

To maintain a balanced life, Perez is a regular at the gym, and he finds relaxation in watching Star Trek reruns. He lives by the philosophy that innovation is the key to progress, and he approaches each day with boundless energy and an unwavering commitment to excellence. His journey is a testament to the remarkable achievements of a truly exceptional individual.

Dr. Joe Perez is Accorded with the following Honors & Awards :

https://www.linkedin.com/in/jwperez/details/honors/

Dr. Joe Perez is Bestowed with the following Licences,Certifications & Badge:

https://www.linkedin.com/in/jwperez/details/certifications/

https://www.thinkers360.com/tl/badge/19985/2764

Dr.Joe Perez is Voluentering in the following International Industry Associations & Institutions :

https://www.linkedin.com/in/jwperez/details/volunteering-experiences/

Dr.Joe Perez can be contacted at :

E-mail | LinkedIn | Web | Sessionize | FaceBook  | Twitter | YouTube

Also read Dr.Joe Perez‘s earlier articles:

The post Sumerian Time to Digital Design appeared first on Industry4o.com.

Data protection by design and default is a key element of the UK GDPR’s risk-based approach and its primary focus is on accountability. According to GDPR, data protection by design and default means “an appropriate technical and organizational controls and measures required to implement the data protection principles and safeguard individual rights”. Privacy by design focuses on embedding privacy protection measures throughout the organizational technical infrastructure including the design, development, build and running for software, products, processes and services to ensure personal data processed by these means is managed, secured, and the risk to the data subject is significantly reduced. The GDPR’s key Article 25 indulge controllers to adopt technical and organizational measures that, by design, implement data protection principles into data processing and protect the rights of individuals whose personal data is processed or utilized.

Article 25 of the GDPR—titled “Data Protection by Design and by Default” is the primary source on the need for designing privacy by default and implement control measures to improve privacy posture of the organization. Implement data-protection principles in an effective manner and integrate the necessary safeguards into the processing in order to meet the requirements of the GDPR and protect the rights of data subjects. Privacy by Design and default means that organizations need to consider privacy from the first design stages and throughout the complete development process of any new processes or services that involve processing of personal data. This means that it is no longer just about data protection but rather about designing and building systems so data is inherently protected.

It’s vital to acknowledge that data privacy is critical and ensure this message resonates throughout the organization. It should be integral to the business culture. From the top down, the importance of user privacy must be encouraged, throughout all business practices and ensure that everyone respects this. Ensure that you design and build in the necessary controls to enable consumers to enforce their privacy requirements and the level of protection that they require. Flexibility ensures that users can provide privacy and data protection for varied conditions and environments to support unique and individual security requirements better.

There has always been a strategy that organizations have been following that “Data is always good, everything is important, collect as much as you can and use it when required.” This thinking needs a change while adapting to GDPR’s data minimization requirement, organizations must limit the data collection, define purpose of data requirement and store it in a secured manner of the required data only. Processing of personal data complies with various restrictions to protect the data and avoid data exploitation or losing the data in large numbers.

Exceptions to the GDPR:

Under the GDPR, there are two significant exceptions to note –

The first exception is for companies with less than 250 employees. Organizations in this category are not fully exempt, but they enjoy a more lenient coverage under the regulation. However, such companies must fully comply with the GDPR when:

• Their processing activities may risk the rights and freedoms of data subjects
• They process sensitive personal data or process data frequently, or
• They process a special data category relating to “criminal convictions and offenses”

Secondly, the GDPR does not apply to individuals or companies involved in purely “personal or household activities”. Its scope only covers “commercial or professional activities.”

Procedures for Responding to Privacy Requests:

A major component of GDPR compliance is responding to data subject requests as they come in. There are several types of requests:

• Access requests
• Deletion requests
• Requests to correct inaccuracies
• Object to processing
• Requests to limit processing
• Opt-out of automated decision-making

Responding to any of these data subject requests can be demanding, and they generally must be completed within a one-month time limit. This requires advance planning on the part of controllers, and failure to put procedures in place will not excuse inadequate or late responses.

Simplified GDPR Compliance:

As the principle of data protection by design makes clear, GDPR compliance is not just cosmetic changes, but, stringent in the way it has to be aligned with the regulatory requirements. It requires vigilant planning and thoughtful action. Each and every GDPR principle has its defined process and steps to follow to ensure data security is embedded at the designing stage itself by default.

Article 25 of the GDPR requires a data protection by design and default, data controllers or data processors or sub processors based on the role that as organization is playing, it must ensure that robust planning is done to put technical and organizational controls in place to define the process of processing personal data. Building compliant process means that the new functionality needs to be embedded within the organization structure in a very structured manner to meet both the organizational policy and regulatory standard requirements to deliver privacy protected services.

Key takeaways to ensure GDPR compliance:

Data Privacy policies should be implemented at a technical and business process level. When personal data is no longer required, it needs to be destroyed or anonymized. Consent management for approving, anonymizing the data, storage of data and other data treatments is an integral part of near-future systems to ensure controlled processes are defined to avoid unauthorized access or data leakage.

Best Practices to safeguard Personal Data:

• Try to prevent crises rather than seeking solutions
• Embrace privacy as the default setting to ensure protection of privacy data
• Integrate privacy into the design and embed it into the Organization policy.
• Privacy should be completely functional
• Protect data throughout its lifecycle
• Complete transparency and lawful processing of data
• Prioritize the protection of individuals information

It’s important to assign responsibility to make sure that the end-user privacy is considered. This needs to be done throughout the whole product life cycle and throughout the different business processes. When collecting personal data and processing the data at various levels, an organization should designate an authorized individual to ensure end-user privacy is built into the services, business processes and monitor the privacy posture on an ongoing basis to ensure data protection.

Disclaimer :

“The views and opinions expressed by Ms. Kavitha Srinivasulu in this article are solely her own and do not represent the views of her company or her customers.”

About the Author :

Ms. Kavitha Srinivasulu
Global Head – Cyber Risk & Data Privacy – R&C BFSI
CCISO | DPO | CISM | CEH | CCSO | CCIO| PCSM | PDPP |

Tata Consultancy Services

Ms. Kavitha Srinivasulu has around 20+ years of experience focused on  Cybersecurity, Data Privacy & Business Resilience across BFSI, Financial  services, Retail, Manufacturing, Health care, IT Services and Telecom domains. She has demonstrated her core expertise in Risk Advisory, Business Consulting and Delivery assurance with diverse experience across corporate and Strategic Partners.She is a natural leader with versatility to negotiate and influence at all levels.

Ms. Kavitha Srinivasulu is a Board Member of Women in CyberSecurity (WiCyS) India

Ms. Kavitha Srinivasulu is an Executive Committee Member CyberEdBoard Community

Ms. Kavitha Srinivasulu is Bestowed with the following Licenses & Certifications :

https://www.linkedin.com/in/kavitha-srinivasulu-5619ab7/details/certifications/

https://www.linkedin.com/in/kavitha-srinivasulu-5619ab7/details/publications/

Ms. Kavitha Srinivasulu can be contacted at :

LinkedIn : https://www.linkedin.com/in/kavitha-srinivasulu-5619ab7/

Also read Ms. Kavitha’s earlier article:

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Introduction

Advancements in technologies are enabling enterprises across the sectors to take notice and embrace them to solve business challenges and drive productivity to stay competitive. These technologies have led the way towards Industry 4.0 (a.k.a) Fourth Industrial Revolution which is a suite of next generation technologies that help solving business challenges and help enterprises become future ready.

Smart manufacturing is a technology-driven approach to optimize all aspects of the manufacturing process using data as the main driver. It uses Industrial Internet of Things (IIoT) to collect, cleanse, store and process data that is generated at each step of the manufacturing process. The data is generated by the process that is being followed, the physical assets involved in manufacturing and even by people who are monitoring and managing the whole process.

A smart system consists of self-aware objects/components with embedded sensors and communicate with each other over a secure network. The data is collected and typically stored in the cloud and can be fed to a digital framework that accurately corresponds to the physical ecosystem described above.

Such a framework or a Digital Twin of the physical realm can be designed to analyse / monitor / diagnose / rectify any anomaly in it. Advanced predictive and prescriptive capabilities based on learning models can pre-empt failures and anticipate unscheduled downtime.

Multiple aspects need to be considered while designing a “Digital Twin”, like its complexity level, physical models (aerodynamics, thermodynamics etc.) it will adhere to and its main functionality. I will address these points in subsequent sections.

What is a Digital Twin?

Let us start with a basic understanding of the concept. A digital twin or DT is a virtual representation that serves as the real time digital counterpart of physical assets/processes such as jet engines, wind turbines, factory floor operations and even whole cities or buildings. Physical object and its virtual counterpart or digital twin is interconnected with a high level of synchronization and interact in a mutually beneficial manner. A real-time data exchange allows continuous update of status information to the virtual object.

The gathered information can then be used to assess operating condition of the physical object, analyse historical data to predict maintenance requirements to avoid unscheduled downtime and monitor its condition by processing sensor data generated in real time.

Advancements in Machine Learning and big data technologies enable these digital models to showcase how corresponding physical systems would respond under a given set of operational scenarios. It helps to identify and prevent costly failures, enhance predictive capabilities, and optimize physical operations.

Another characteristic of DT is that these technologies leave digital traces. These traces can be used by engineers for example, when a machine malfunctions, to go back and check the traces of the digital twin, to diagnose where the problem occurred. These diagnoses can in the future also be used by the manufacturer of these machines, to improve their designs so that these same malfunctions will occur less often in the future.

What are the benefits of using a Digital Twin?

• Remote monitoring in real time – critical parameters of valuable assets can be monitored in real time for any anomalies and to optimize its performance.
• Predictive maintenance – large amounts of data is generated through the physical asset sensors which is then analysed for any pattern to identify problems in the system proactively.
• Rapid assessment – Engineers can test different operating models for their asset, simulate and test scenarios before deploying it on physical systems.
• Analysis of operational history – Pattern finding in the past data or digital traces can help to predict similar outcomes in future and can be planned well in advance.

What is different this time?

The concept of Digital Twin is not new. There are different avatars of digital representations of physical objects that have been actively used for a long time. Digital models developed using CAD accurately capture dimensional details and tolerance bands of the object to be constructed. Simulation software use mathematical representation of universal principles of Physics like thermodynamics, computational fluid dynamics to simulate situations and see how the proposed object would behave. Data historians store time series data generated by the process monitoring systems that can be analysed further to improve operational performance.

One big difference between these technologies and digital twin is the real time synchronization of data between the physical object and its digital model through an interconnected network of Internet of Things (IoT). Hundreds of sensors gather data on different operational and physical parameters, edge devices process the information before sending it to the cloud for digital twin to update its status and remain in sync with the exact state of the physical object. The main difference between these technologies is the interaction and exchange of data between the physical object and the digital model. I will describe further to help you understand better.

On the prediction front, the major difference between a digital twin and a simulation is that the former has a two-way data interconnection with the physical model and uses the current and historic data to make predictions on the system behaviour, while simulation predicts the future state of a physical system based on a set of assumptions and its own dataset. It does not consider the real data captured from the very same physical object it is predicting about. A digital twin plugs this gap and make predictions with far more accuracy.

Simulation models can complement digital twins with their computational capabilities and in-built models for thermodynamics, aerodynamics etc. and provide additional decision-making information to the digital twin.

Key Considerations

There are several factors to consider while ideating and designing a digital twin for optimum performance. The solution should not only address the business problem but do it with maximum efficacy. The essence of a successful digital twin is to capture the right context in which the underlying physical asset is functioning. For example, a solenoid valve used in application A will operate and behave as per the ambient configuration while another valve with a different specification is used for application B and is expected to operate under a different configuration. A well-designed DT system should be able to differentiate between the two instead of treating those in a generic manner.

Secondly, accurate sensing is a must for a digital twin to be effective. Right type and specification of sensors need to be identified for data capture and their calibration should be done on a regular basis to ensure best data quality.

Designing a Digital Twin

A bottom-up approach should be taken to know the physical object in the minutest detail possible, including its static properties. But before that there should be a clarity on the functional specifications and its decomposition and what the system intends to do. It can be purposed to optimize the operation, monitor for potential anomaly or make predictions on the future state or a combination of these functionalities. The next step is to identify the parameters that need to be captured to implement the aforesaid functionalities.

Once the parameters are identified, the focus shifts to how these values will be captured from the physical system. Shortlisting or sensors, communication protocols, processing need of captured data at the edge device. data connection between the physical and digital object and the complete flow should be designed. For example, if the primary job of the digital twin is to optimize operation, then it should be able to capture the relevant data needed for cost analysis, efficiency monitoring etc. along with the data techniques that would be deployed to do so. Say, if operational efficiency of a turbine needs to be monitored then the its emission levels need to be monitored or how well it is combusting fuel to generate the required output.

The physical object is monitored by sensors and data is collected, processed and stored in real time. Using this data, the digital twin can assess operational condition and predict maintenance requirements by using Machine Learning models. As the data is gathered over time, it can be analysed to detect patterns that can help to identify product design problems and suggest improvement.

An important part of a digital twin is to design and develop virtual models that capture information from various aspects of the physical object. Structural model captures the dimensional aspect of the object along with geometries and permissible tolerance levels while behaviour models are based on laws of Physics and capture how the physical object reacts and responds to the environment. Data models maintain all the variables that reflect reality at a given level of abstraction. These models need to be fine tuned and validated individually before they are unified under a digital twin. The whole system then needs to work seamlessly and interact with each other as desired. The complexity of developing it is a huge task and demands a well-knit group of people with the right skill sets who can work as a team to design, develop, validate and optimize the digital twin solution. These are the biggest challenges to design and deploy a digital twin successfully.

Conclusion

Digital twin approach opens new possibilities to provide autonomy for manufacturing assets and interacting processes. Self-aware digital models can monitor, analyse, predict and even prescribe optimal steps to operate critical manufacturing assets and processes. However, a methodical approach is needed to define and develop a digital twin to reap the maximum benefit from the significant investment to be made in technology and human resources. In order to test the waters, it is advisable to start with a smaller but important component in your manufacturing ecosystem. That way it would be easier to secure a buy-in from the senior leadership and the Return on Investment (RoI) can be maximized and showcased to gain confidence for more complex and resource intensive projects.

About the Author :

Mr. Vishal Kelkar
Senior Product Strategist – FIS

Vishal Kelkar is a certified digital manufacturing and smart factories specialist from Indian Institute of Science (IISc), Bengaluru, India. He has 22+ years of business consulting experience and has extensively worked in the areas of product strategy and management, business solutions consulting and industry thought leadership. He has authored business articles, whitepapers and point of views published across industry magazines and blogs.

Mr. Vishal Kelkar is Bestowed with the following Licenses & Certifications :

https://www.linkedin.com/in/vishal-kelkar/details/certifications/

Mr. Vishal Kelkar can be contacted at :

E-mail  | LinkedIn | Twitter

The post Digital Twin Design appeared first on Industry4o.com.

Introduction

The follies associated with misunderstood requirements and misplaced designs in software engineering are well known. The mistakes in the early stages of software development are quite expensive and vexing to resolve. Multiple techniques are used to avoid these situations such as wireframes, Drawings of various sorts, elaborate documents, Inspection/reviews etc. However, it is not always easy to visualize what is in the minds of various stakeholders, until the D-Day. It is especially true in the case of visually intensive and interactive applications.

In principle, the immersive nature of Metaverse is ideal in the early stages of software design. It should eliminate the difference in perception of various stakeholders and help arrive at the ‘what you see is what you get’ stage quickly.

We tried to put these expectations to test for requirements elicitation and finalization of design alternatives. The results are encouraging and show what we can achieve with current state of Metaverse technologies.

Case Study – Automotive Cockpit design

Designing an automotive cockpit is quite involved. Apart from considering OEM-specific design cues, variant-specific display sizes and capabilities, it is quite difficult to convey the expected result in various lighting conditions, viewing angles and distances etc. until quite later in the development cycle. With distributed teams participating in design and decision-making process, the situation only gets worse.

With Virtual reality, it is possible to alleviate some of these issues. The design alternatives can be modeled and deployed in VR headsets, providing a better feel for the design. However, it is not possible to ensure all users view the same design in the same conditions/settings. A voice sync would be another challenge for a real-time discussion.

As we moved to Metaverse, multiple stakeholders could simultaneously critique the design under same conditions – for example, they could switch the seats to view the cockpit from different angles, change the day/night lighting conditions, play videos, and change color scheme etc. They could also discuss with each other and interact with the design environment. This provided a genuinely immersive real-time interaction with design alternatives and the decisions could be made more confidently.

Few things to keep in mind while adapting to Metaverse:

While some Metaverse platforms allow interactions from Desktop/Mobile apps, it is recommended to use a VR headset for a real feel of the design. Low graphics quality on desktops would ruin the effort of the initiative. Having said that, it is preferable to choose a platform that also supports desktop/tablet to cater to longer discussions and to involve users who are not comfortable with wearing headsets.

Consider Data security and Intellectual Property issues for the content uploaded to a Metaverse platform. If you are finicky, there are alternatives to true Metaverse platforms, requiring a bit more effort from users to install some apps on their devices. However, these are not insurmountable issues. Consult with a technical expert to understand the options and limitations. Our goal is to improve product requirement elicitation and design experience rather than true Metaverse adoption!

Initial trials could take a while. Engaging with a Metaverse development partner, adopting to using the VR headsets, populating design assets – all these activities require time. However, this would pay off in the subsequent iterations, once the process is established and initial assets are populated.

Building enthusiasm for Metaverse with target stakeholders would help. They should be prepared to brave the possible initial discomfort in working with VR headsets. This initiative should be treated similar to any Digital Transformation initiatives in the organizations, with users at the center.

Initial investments are required for the VR headsets and design efforts. However, the overall initiative is not prohibitively expensive. In addition, it pays off in the long run through:

Reusable design elements/assets, leading to reduced cycle time for new design variants.

Reduced iterations for design discussions and longer approval cycles.

Reduced defects due to assumptions, implicit requirements etc.,

Increased customer confidence and a happy design team

There are multitude of scenarios where Metaverse could be useful during collaborative product design. Distributed teams will be quite benefited to be in the same space as their colleagues and interactively design a product. Stakeholders can participate in design discussions quite effectively, from anywhere and just with a VR headset, rather than requiring machines with high performance graphics and design environments.

Final Thoughts

While experts suggest that the true Metaverse is a few years away, there are real-world use cases where we can experiment with Metaverse today. It is useful to test and adopt what works for a given use case rather than waiting for the maturity of the technology to its altruistic form.

Improvements in the VR headset design and cost, newly found interest for metaverse in the recent years and the euphoric analyst reports about the future of the Metaverse may be the right conditions to start your journey

About the author :

Mr. Bhaskara Srihari Vangaveti
Enterprise Architect | IoT Consultant
Cloud Computing | 5G | Metaverse
Chief Expert
Bosch Global Software Technologies

Srihari is a TOGAF certified enterprise architect and consultant for IoT and Digital transformation initiatives. He has over 25 years of experience in varied roles, including customer engagement and consultancy, Blue printing, Solution and Technology architecture, and Technical Sales. His experience includes engagements in Enterprise applications, Industry 4.0, Connected Products and Connected Car domains across Europe and APAC.

Srihari is a technology enthusiast and is playing an active role in exploring Metaverse and 5G technologies. As a Chief Expert at CTO office, he is responsible for fostering innovation and scanning of emerging technology landscape.

Mr. Bhaskara Srihari V  is Bestowed with the following Licenses & Certifications :

https://www.linkedin.com/in/bhaskarasrihari/details/certifications/

Mr. Bhaskara Srihari V can be contacted at:

Email : Bhaskara.Srihari@in.bosch.com / sriharivb@hotmail.com

LinkedIn : https://www.linkedin.com/in/bhaskarasrihari/

Twitter : https://twitter.com/sriharivb

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As per the World Economic Forum, The Fourth Industrial Revolution represents a fundamental change in how we live, work, and relate. It is a new chapter in human development, enabled by extraordinary technological advances commensurate with the first, second, and third industrial revolutions.

In the Fourth Industrial Revolution, companies are redefining – how products are designed and manufactured, raw materials are sourced, and services are offered by connecting each link in the supply chain

“To remain competitive, both companies and countries must be at the frontier of innovation in all its forms, which means that strategies that focus on reducing costs will be less effective than those based on offering products and services in more innovative ways.”

– The Fourth Industrial Revolution, Klaus Schwab.

Importance of Sustainable Product Design?

Now, Sustainability is no longer a nice to have a topic; sustainability has become a business imperative. As per G&A Institute, In 2011, only 20% of S&P 500 companies reported their ESG scores. Today a whopping 92% do.

The green line is as important as the top and the bottom line for companies, employees, and investors. The need is – How to make sustainability profitable and profitability sustainable.

Product design plays a significant role in reducing a company’s overall environmental impact. As per McKinsey’s recent report,

Up to four-fifths of a product’s lifetime emissions are determined by decisions made at the design stage. By building on proven cost-optimization techniques, companies can get those choices right.

Traditionally, product design decisions are made to optimize the manufacturing & sourcing cost of the manufacturer and the operation & maintenance cost of the end-user. The same thought process can be applied to product sustainability, such as product repair, upgrade, remanufacturing, and recycling at the end of life.

Companies’ fundamental sustainability goal is to design recyclable and environmentally sustainable products.

For example, plastics such as PET and HDPE are relatively easy to recycle, whereas the commonly used polystyrene and PVC are tough.

If every product were designed with sustainability as a priority, the environmental impact of manufactured products could be reduced to around 20% of its current level.¹

Sustainable Product design impacts every step in the supply chain. Companies are now adapting their product design to minimize waste and maximize re-usability. This is helping companies bring recyclable & environmentally sustainable friendly products from the initial phase of product design to the end-of-life of the product, assisting companies to transition into the circular economy.

How does sustainable Product Design decision help companies on their sustainability journey?

With the product design at the core, companies aim to achieve efficiency, minimize risk and protect their & their customer’s brands from all aspects of compliance applicable to product materials or ingredients.

To manage the carbon footprint of the products, companies need to Understand the CO₂ footprint of inputs and operations, optimize operations (Supply Chain and Manufacturing) based on benchmarks, and transform into new business models & product portfolios while optimizing the total CO₂ footprint.

Product design decisions impact the entire product lifecycle in the following lines.

• Input materials:
  • Optimize the input materials. Sourcing decisions across the supply network (e.g., sourcing raw materials with a low carbon footprint and sourcing locally to decrease transportation emissions and costs).
  • Increase the utilization of the re-used components without compromising quality. Set targets on how much re-usable input components must be used (e.g., 25%).
• Transportation :
  Design packaging that keeps products safe throughout their transport and avoids harmful packaging materials.
• Re-design processes :
  Re-design production processes to remove wastefulness from every step of your production. Production process decisions made during product design help optimize energy usage & reduced emission during production.
• Operate & dispose of :
  Design the product to ensure that the product itself or components can be re-used in a commercially viable manner.
• Business innovation :
  Weigh design decisions to shift to new business models (i.e., Product as a Service) for longevity, collaborative maintenance / remote diagnosis, ease of re-manufacture, etc

How does SAP Helps?

SAP’s goal is to Integrate sustainability data into business processes across all value chains to drive performance, new products, and new markets. This is helping companies in getting the clarity into their green line.

SAP’s new offering, the SAP Cloud for Sustainable Enterprises, brings together a comprehensive portfolio of solutions that enables businesses to holistically manage sustainability performance.

Here are a few critical solutions to helping companies on their Sustainable Production Design journey.

SAP Responsible Product Design helps companies calculate extended producer responsibility (EPR) obligations, plastic taxes, and corporate commitments to optimize material choices. The solution accesses your enterprise or third-party system data and combines it with information on global regulations to calculate obligations in key markets.

SAP solution Product Compliance helps companies to manage regulatory requirements, track substances, assess supplier materials, classify products, and manage and ship compliance documents. This helps to ensure product compliance and safety and builds controls throughout the product lifecycle.

Stakeholders can efficiently manage regulatory and customer requirements, create compliance documents, manage dangerous goods, and provide compliance information to all stakeholders.

SAP Enterprise Product Development gives companies the flexibility to reimagine their design processes. Empower the companies to innovate, iterate and introduce new products through closed-looped insights, processes, and people. This helps to capture the voice of your customer and analyze and simulate your product design with insights through IoT and Machine Learning. By providing integrated visibility to market demand, product configuration requirements, and business information, SAP Enterprise Product Development compresses the idea to the product cycle, enabling faster innovation and increasing time to value while reducing costs.

SAP Product Footprint Management helps companies gain insights on their products’ environmental impacts across the entire lifecycle for disclosure and internal product & process optimization. The solution integrates into SAP Integrated Business Planning, helping supply chain planners select the sourcing decision based on the material having a lower carbon footprint.

What are the benefits with Sustainable Product Design approach?

• Design products that are recyclable and environmentally sustainable
• Ensure high and automated transparency of product compliance requirements​
• Holistic Product lifecycle Costing including social and environmental aspects​
• Seamless handover to manufacturing and efficient supplier collaboration
• Reduce exposure:
  Calculate fees and taxes accurately and implement measures to reduce regulatory costs.
• Lowers the Carbon Footprint across the supply chain: Product Carbon Footprint details, once integrated into the Supply Chain Planning system, help planners make the sourcing decision based on the material having a lower carbon footprint.

How to proceed?

• Start Transformation:
  Gain insight by aligning people, processes, and technology to holistically manage sustainability aspects across your enterprise and the supply chain.
• Get a baseline and identify the hot spots for improvement:
  Assess how you perform – environmental, social, and governance impact.
• Focus:
  Set the overall direction of where you want your company to go. Identify impact areas, and define targets, milestones, and timelines.
• Sustainability Performance:
  Monitor, measure, analyze and report on improvements around sustainability performance

For more information on how SAP can help to accelerate your sustainability journey, please visit the following home page:

1. Enable resilient and sustainable supply chain management processes:
Enable your company to stay resilient, agile, productive, and connected with our sustainable supply chain management software.

2. Experience SAP Industry 4.Now

3. Sustainable business solutions and services from SAP

My Past blogs on Sustainability published in Industry 4.0 Manufacturing Online Magazine
Industry 4.0 helps manufacturing companies accelerate their sustainability journey

Reference:

1. Sustainability in Product Design: Plastic and Packaging

2. The Fourth Industrial Revolution, Klaus Schwab

3. Product sustainability: Back to the drawing board

4. G&A Institute Research on Published Sustainability Reports in 2020

About the Author:

Mr. Satya Narayan Sahu
Senior  Director, Industry 4.0, Digital Supply Chain, and Sustainability

SAP Asia Pte Ltd

Satya Narayan Sahu has over 20 years of software industry experience in Industry 4.0 Digital Supply Chain, Manufacturing, and Sustainability.

In the current role, Satya works with manufacturers, system integrators, and start-ups in the region to drive innovation in Industry 4.0.

Before this role, Satya has played various positions in product innovation and go-to-market of SAP’s Industry 4.0 solution portfolio.

Satya has also co-authored two books on Manufacturing IoT – “Manufacturing Operations Management:” “The Hitchhiker’s Guide to Operations Management: ISA-95 best practices Book 1.0”, and “When Worlds Collide in Manufacturing Operations: ISA-95 Best Practices Book 2.0

He can be contacted at :

LinkedIn : satyansahu

Twitter : satyasahu

Also read his earlier article:

The post Sustainable Product Design appeared first on Industry4o.com.

These are famous words by Jonathan Ive, the legendary former Chief Design Officer at Apple. We resonate with the thought. It inspires us. It helps us better understand “Growth Mode Design”, when put into perspective.

The Design Context

Becoming better than others is indeed very difficult in today’s competitive era. More so when it comes to Design, as technology advancements rapidly redefine business landscapes and the tools for visual expression leap forward to catch up with human ingenuity and imagination.  But it’s not impossible – as demonstrated by Jonathan Ive. Being conscious about the eco-system around the Design and the impact created by it on the elements of the eco-system are very important here.

Before advancing the “Growth Mode Design” discussion, let us understand what it is and how is it different from conventional Design.

The Approach

The growth oriented Design approach takes a holistic look at the problem at hand. It then attempts to create a viable solution, which addresses the need of all key stakeholders. It aligns user experience and its business impact to the organizational goals. As per the Growth Design approach, Design is not an after thought brought in to merely give visual expression/deliver the UI. It is integral to the core activity of identifying growth opportunities; ideation – which factors in the user research; planning the A/B tests and strategic decision making.

Growth Mode Design is considered to be achieved when Design dynamics meet business growth needs. It is a methodology to create favorable business outcomes with the help of successful Design.

What it Takes

Growth Mode Design calls for resources with a wide range of skills and traits, including empathy, research, conceptualization, prototyping, analytics and testing, data analysis, visual Design, software development, marketing, branding, and sales– all aligned to the approach. Needless to mention the importance of an organizational culture that supports the process which can throw up timeline challenges and deadline scares.

Key Stakeholders and How the Growth Mode Design Impacts Them

Internal Stakeholders

• Management – helps the management in progressing towards the fulfillment of company’s vision
• Product Management – helps in supporting the organization’s overall strategy and business goals
• Operations – helps in producing the product/service of the right quality, within the optimal time and at the optimum cost, to meet the customer and business expectations
• Marketing – helps in successfully promoting the brand/product/service and generate the desired business leads/hits/footfalls
• Sales – helps in achieving the sales targets and generate revenue for the organization as per the business goals

 External Stakeholders

• Customers – helps in meeting the expectations in a timely manner at the desired price point and with a delightful (purchase) experience
• End Users/Consumers – helps in meeting the need/want for the product with a pleasant (user) experience
• Shareholders & Investors – helps in moving towards meeting the shareholder objectives
• Competitors – helps in bench marking their products/services and facilitates sector development/advancement
• Partners – helps in strengthening and advancing the win-win association

The Growth Mode Design approach is gaining wide acceptance these days as competition intensifies and “being better” becomes more important than “being different”. Amazon, Uber Eats, Airbnb, Spotify, Duolingo, Adobe, Ola, Hike, Meesho, PhonePe, and Trello are few outstanding examples here.

About the Authors:

Mr. Ramachandran Thencheri
Co-Founder & CEO

Beanpole

LinkedIn : ramthencheri

A result oriented marketing and communications professional with over 20 years of experience in spearheading Marketing, Branding and Communication activities. Ram has had successful stints across the industry sectors of media, consulting, financial services and ed-tech during his career.

During the immediate years preceding the co-founding Beanpole, Ram had helped clients on marketing and communications, focusing on ideation and content creation, as an independent consultant.

Mr. Harshit Kumar Gupta
Co-Founder & Director-Experience Design

Beanpole

With exposure in corporate and academic domains, Harshit is equipped with design and management skills alike. He has completed M. Des from Indian Institute of Science, Bangalore, after securing AIR-22 in GATE 2015. He has founded a popular social networking platform which helps students to gain admission into India’s prestigious institutions.

He has worked on a number of projects such as redesigning of a warehouse vehicle, an ingress-egress system for the elderly and a patient transfer system. He likes to mentor people on design projects to improve the functionality, usability and aesthetics of a user-centric system.

The post Growth Mode Design appeared first on Industry4o.com.

With Industry 4.0, digitalization of process and introduction of cyber-physical systems enables automation and real-time access to data for intelligent decision-making. Intelligent workflows not only helps in digital modeling of processes, but also enable Intelligent analytics, decision-making and process automation. As and when required, this also uses exponential technologies such as robotic process automation (RPA), intelligent chatbots, predictive and prescriptive analytics, IoT, Blockchain and so on.

As an example, consider the process of manufacturing a special purpose machine designed and manufactured by a company in engineering industry. This is a complex manufacturing scenario where the product is completely designed, configured, and assembled based on specific customer specification. The process starts with the customer enquiring for a product with a specific set of requirements which is the lead generation process which triggers the engineering and product design process through a project system created for complex products with multiple parts and sub-assemblies which need to be designed, configured or procured based on the specifications provided within a defined cycle time. After the initial design the product price quotation is created and through an approval/review process it is converted to a sales order. Once the customer accepts the same., this triggers the manufacturing process which involves the detail product design, production planning, manufacturing execution and assembly, procurement and subcontracting and finally installation and commissioning of the product at the operations site which is usually done for large equipment. This in turn leads to the service initiation, billing and finally the after-market service operations to provide continuous service as per the contract and warranty conditions.

Here as we see the end to end process which consists of multiple sub-processes such as Lead to Order, Complex Assembly & Manufacturing, Handover & After Market Service. All of these are interconnected to each other with multiple granular sub-processes under them, spanning across different IT systems and departments inside the organization and even beyond.

Assume if a product issue is reported during the operation of this special purpose machine in field, the OEM will like to find the root-cause of the problem which may be due to a specific design consideration, or specific components procured from a specific vendor, or a specific issue during manufacturing of the product. Now with the absence of a process model and digital thread it may not be possible to easily trace back to the root-cause of the problem as this involves many manufacturing stages, multiple subcontractors and vendors. With Industry 4.0, the above issue can be easily addressed by two parallel approaches namely – defining the digital process model for the end to end process and introducing IoT and digitalization as much as possible leveraging the exponential technologies. This will in turn enable to realize the digital thread across the process-chain which will not only provide end to end visibility of the process at any point of time, but also using the data mined across the process to enable automation and process improvements with intelligent actions and helping to reduce cycle time and improve product quality and customer satisfaction.

At different steps of this value-chain, certain intelligent actions can be infused levering the exponential technologies and Industry 4.0 concepts.

For example in  lead generation process, intelligent bots can be developed to consume the news and stock information to determine the potential customers who might be starting an expansion or modernization initiatives for their manufacturing facilities and need specific equipment depending on their business need. Intelligent chatbots can be used to validate the demands with the customers and automatically generate sales lead which triggers the engineering design and project creation based on the previous customer data and derive pricing of the product intelligently by cognitive analytics.

Once the quotation is approved by the customer, sales order is created automatically through the intelligent workflow and triggers the planning and manufacturing process which also should implement the cognitive planning process and intelligent procurements processes to determine the most optimized planning and procurement or subcontracting options, considering the various factors such as environment, transportation, cost, reliability, etc.

Intelligent workflow can also help in intelligent trigger of preventive actions before asset breakdown happens or nonconformance happens in shop resulting in quality rejection.

Intelligent workflows can also be triggered from supply chain control towers when an end to end process KPI shows unacceptable performance and hence provides quick proactive action to bring back the process performance to intended values.

To define Intelligent workflow for such a complex manufacturing and After service set up, following steps, need to be followed as shown in Figure

• Model the process and sub-processes by Design Thinking workshops with end users and process mining across relevant systems by using specific tools available for the same
• Develop the actual workflows based on the process model across the IT systems levering cross-system workflow management tools. Infuse intelligence and automation using the exponential technologies wherever possible
• Create the process variants if needed to address different variations of the process
• Define the process KPIs across the workflow
• Define and create business rules which provides flexible rule management by end users to control the processes
• Publish the process as APIs for easy consumption by end users and from different triggering points
• Use the process KPIs and feedback from end users to continuously improve the process

Intelligent workflow is the most promising approach to deliver value from organization’s industry 4.0 initiative. It will be wrong to assume this just another new technology as this is a new way of working. As Industry 4.0 concepts are getting extended beyond shop floor increasingly with emerging domains like Logistics 4.0 or Procurement 4.0 – Intelligent workflow can also be adopted for processes beyond manufacturing like Procure To Pay, Order To Cash and Record to Report.

About the Authors

Mr. Rajesh Ray is an Associate Partner & Lead – Digital Supply Chain Practice @ IBM India Pvt. Ltd.,
He is an Engineer + M.B.A. and have 23 Years of consulting and domain experience in supply chain. He had worked in manufacturing and supply chain domain in ITC and Exide Industries. He started his supply chain consulting career with i2 Technologies followed by SAP AG in Germany and for last ten years with IBM. Rajesh is author of three books and 55 articles in different supply chain journals. He is honorary member of CII Logistics and SCOR society.

Mr. Rajesh is an IBM Industry Academy Member, Adjunct Professor of IIT Kharagpur, Principal Digital Supply Chain Architect – PMI, Global Logistics Innovation Lead – Nestle and is a frequent speaker in different supply chain forums.

He can be contacted at:

Mobile: + 91 9830678171 | E-Mail : rajesray@in.ibm.com

Mr. Dipankar Saha

Principal Architect (Industry 4.0)
Incture Technologies

Mr. Dipankar Saha is an IT Architect having 20+ years of experience with specialization on Industry 4.0 & IoT solutions, SAP Manufacturing, Microservices & Cloud Applications Development and Intelligent Workflows.

He is experienced in defining architecture and leading implementation of Industry 4.0 solutions for manufacturing execution, analytics, and integration and has led several large and complex Industry 4.0 implementations globally as well as worked on product development.

He has co-authored several professional books on SAP Manufacturing solutions (SAP MII, ME, OEE) which have been published from renowned publishers e.g. SAP Press, Apress & WisPubs and published whitepapers in online journals.

Currently he works at Incture Technologies as Principal Architect.

Mr. Dipankar Saha is Bestowed with the following Licenses & Certifications :

https://www.linkedin.com/in/dipankarsaha/details/certifications/

Mr. Dipankar Saha can be contacted at :

e-mail | LinkedIn | Twitter

Also read Mr. Rajesh Ray earlier article :

The post Intelligent Workflow Design for Industry 4.0 appeared first on Industry4o.com.

PLM brings together people, data processes and business systems and provides a product information backbone for companies and their extended enterprise.

The five long-term objectives that should be considered in production systems are:

• • Cost Reduction
  • Improved Productivity
  • High end-product Quality
  • Flexibility
  • Sustainability

Finding the Bliss point:

Finding a balance between various stages and processes implemented in PLM processes can be tricky as the stages however subsequent, have components which are quite different from each other.

We need to find a set of techniques which are lean, green and sustainable. Hybrid Processes (both additive and subtractive) in combination with the efficiency bench mark lean processes like multi-directional product production and scaling would be a beginning point. Using eco-friendly models, renewable and non-conventional energy resources would also need to be incorporated in this strategy.

It is quite complex to achieve a perfect balance but this elusive bliss point will bring about achievable efficiency standards and lend competitive edge to the corresponding organization.

The post Design and PLM Processes: Finding The Bliss Point appeared first on Industry4o.com.